EM sovereign bond allocation with macro risk premium scores

March 29, 2025

Jupyter Notebook

Macro risk premium scores are differences between market-implied risk and point-in-time quantified macroeconomic risk. Two principal types of scores can be calculated for credit markets: spread-based risk premium scores and rating-based risk premium scores. This post proposes a small set of these scores for EM foreign-currency sovereign debt, targeting 24 country sub-indices of the EMBI Global. The macroeconomic component captures four risk dimensions: general government finance, external balances, international investment flows, and foreign debt sustainability.
Macro risk premium scores are constructed on a point-in-time basis, making them suitable for backtesting. Both individual and aggregated scores have shown strong and statistically significant predictive power for subsequent returns of country indices. Portfolios of EM sovereign bonds weighted by risk premium scores have consistently outperformed those based on equal weights or risk parity. Risk premium scores have also generated material cross-country relative value. Most importantly, macro risk premia offer a responsible and profitable approach to adjusting weights of emerging market bond indices.

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Classifying credit markets with macro factors

February 15, 2025

Jupyter Notebook

Macro credit trades can be implemented through CDS indices. Due to obligors’ default option, long credit positions typically feature a positive mean and negative skew of returns. At the macro level, downside skew is reinforced by fragile liquidity and the potential for escalating credit crises. To enhance performance and create a chance to contain drawdowns, credit markets can be classified based on point-in-time macro factors, such as bank lending surveys, private credit dynamics, real estate price growth, business confidence dynamics, real interest rates, and credit spread dynamics. These factors support statistical learning processes that sequentially select and apply versions of four popular classification methods: naive Bayes, logistic regression, nearest neighbours, and random forest.
With only two decades and four liquid markets of CDS index trading, empirical results are still tentative. Yet they suggest that machine learning classification can detect the medium-term bias of returns and produce good monthly accuracy and balanced accuracy ratios. The random forest method stands out regarding predictive power and economic value generation.

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Tracking systematic default risk

December 30, 2023

Systematic default risk is the probability of a critical share of the corporate sector defaulting simultaneously. It can be analyzed through a corporate default model that accounts for both firm-level and communal macro shocks. Point-in-time estimation of such a risk metric requires accounting data and market returns. Systematic default risk arises from the capital structure’s vulnerability and firms’ recent performance, as reflected in equity prices. The metric is both an indicator and predictor of macroeconomic conditions, particularly financial distress. Also, systematic default risk has helped forecast medium-term equity and lower-grade bond returns. This predictive power seems to arise mostly from the price of risk. When systematic default risk is high, investors require greater compensation for taking on exposure to corporate finances.

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Sovereign debt sustainability and CDS returns

November 4, 2023

Selling protection through credit default swaps is akin to writing put options on sovereign default. Together with tenuous market liquidity, this explains the negative skew and heavy fat tails of generic CDS (short protection or long credit) returns. Since default risk depends critically on sovereign debt dynamics, point-in-time metrics of general government debt sustainability for given market conditions are plausible trading indicators for sovereign CDS markets and do justice to the non-linearity of returns. There is strong evidence of a negative relation between increases in predicted debt ratios and concurrent returns. There is also evidence of a negative predictive relation between debt ratio changes and subsequent CDS returns. Trading these seems to produce modest but consistent alpha.

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How to estimate credit spread curves

February 19, 2022

Credit spread curves are essential for analyzing lower-grade bond markets and for the construction of trading strategies that are based on carry and relative value. However, simple spread proxies can be misleading because they assume that default may occur more than once in the given time interval and that losses are in proportion to market value just before default, rather than par value. A more accurate method is to estimate the present value of survival-contingent payments – coupons and principals – as the product of a risk-free discount factor and survival probability. To this, one must add a discounted expected recovery of the par value in case of default. This model allows parametrically defining a grid of curves that depends on rating and maturity. The estimated ‘fair’ spread for a particular rating and tenor would be a sort of weighted average of bonds of nearby rating and tenor.

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Factor timing

April 18, 2020

Factors beyond aggregate market risk are sources of alternative risk premia. Factor timing addresses the question when to receive and when to pay such risk premia. A new method for predicting the performance of cross-sectional equity return factors proposes to focus only on the dominant principal components of a wide array of factors. This dimension reduction seems to be critical for robust estimation. Forecasts of the dominant principal components can serve as the basis of portfolio construction. Empirical evidence suggests that predictability is significant and that market-neutral factor timing is highly valuable for portfolio construction, over and above directional market timing. Factor timing is related to macroeconomic conditions, particularly at business cycle frequency.

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The mighty “long-long” trade

July 13, 2019

One of the most successful investment strategies since the turn of the century has been the risk-parity “long-long” of combined equity, credit and duration derivatives. In a simple form this trade takes continuous joint equal mark-to-market exposure in equity or credit and duration risk. A simple passive portfolio in the G3 would have outmatched most macro hedge funds since 2000, with a Sharpe ratio well above one and not a single annual drawdown. There have been three apparent contributors to this success: undiversifiable risk premia, implicit subsidies paid by central banks, and great diversification benefits from negative return correlations. These forces remain largely in place, but setback risks bear careful watching: excessive leverage in duration exposure, exhaustion of downside scope for yields, attempts of monetary policy normalization, and the possibility of a fundamental shift in macroeconomic policy regimes.

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The dollar as barometer for credit market risk

March 9, 2019

The external value of the USD has become a key factor of U.S. and global credit conditions. This reflects the surge in global USD-denominated debt in conjunction with the growing importance of mutual funds as the ultimate source of loan financing. There is empirical evidence that USD strength has been correlated with credit tightening by U.S. banks. There is also evidence that this tightening arises from deteriorating secondary market conditions for U.S. corporate loans, which, in turn, are related to outflows of credit funds after USD appreciation. The outflows are a rational response to the negative balance sheet effect of a strong dollar on EM corporates in particular. One upshot is that the dollar exchange rate has become an important early indicator for credit market conditions.

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Equity values and credit spreads: the inflation effect

December 29, 2018

A theoretical paper shows that a downward shift in expected inflation increases equity valuations and credit default risk at the same time. The reason for this is “nominal stickiness”. A slowdown in consumer prices reduces short-term interest rates but does not immediately reduce earnings growth by the same rate, thus increasing the discounted present value of future earnings. At the same time, a downward shift in expected inflation increases future real debt service and leverage of firms and increases their probability of default. This theory is supported by the trends in U.S. markets since 1970. It would principally argue for strategic relative equity-CDS positions inversely to the broad trend in expected inflation.

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Credit market herding and price distortions

December 10, 2016

Corporate credit markets have historically been especially prone to herding. The main drivers of herding have been past returns, rating changes and liquidity. Sell herding has been particularly strong and flows have been disproportionate after very large price moves. Herding can be persistent and lead to significant price distortions. Non-fundamental price overshooting is a valid basis for profitable contrarian trading strategies.

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asset management Asset Purchase Program banks bond returns bond yields bubbles capital regulation carry China collateral commodities credit returns default ECB economic data EM equity returns euro area crisis Fed financial crisis FX FX interventions FX returns government debt government deficits herding inflation information insurances Japan leverage liquidity machine learning market turmoil price factors regulation risk management shadow banking statistical methods term structure trend following variance risk premium VIX volatility ZLB
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Macrosynergy is a London based macroeconomic research and technology company whose founders have developed and employed macro quantamental investment strategies in liquid, tradable asset classes, across many markets and for a variety of different factors to generate competitive, uncorrelated investment returns for institutional investors for two decades. Our quantitative-fundamental (quantamental) computing system tracks a broad range of real-time macroeconomic trends in developed and emerging countries, transforming them into macro systematic quantamental investment strategies. In June 2020 Macrosynergy and J.P. Morgan started a collaboration to scale the quantamental system and to popularize tradable economics across financial markets.

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